Data/Metadata Engineer - Everforth ECS

OpenTalent; Arlington (VA); Hybrid; USD 110,000 - 150,000; Full time

Job summary

Everforth ECS is seeking a Data/Metadata Engineer to design, develop, and optimize data pipelines, metadata repositories, and data governance solutions in a hybrid Arlington, VA setting. The role focuses on data quality, discoverability, lineage, and integration across a complex data ecosystem.

Ideal candidates bring strong data engineering skills combined with metadata management, data governance frameworks, and cloud data platform experience to support enterprise analytics and governance

Qualifications

• Experience designing and building scalable data pipelines.
• Hands-on with metadata repositories and data catalogs.
• Strong knowledge of data governance frameworks and lineage.
• Familiarity with Azure, AWS, or Google Cloud data services.
• Proficiency in data modeling for data warehouses/lakes/lakehouse.

Responsibilities

• Design, build, and maintain scalable data pipelines and ETL/ELT processes.
• Integrate data from multiple sources into enterprise data platforms.
• Develop and optimize data models, warehouses, and lakehouse architectures.
• Implement automation and monitoring for data ingestion and processing workflows.
• Maintain metadata repositories, cataloging, and lineage capabilities.

Skills

Data engineering

Metadata management

Data governance

Cloud platforms

ETL/ELT

Data modeling

Job description

Everforth ECS is seeking a Data/Metadata Engineer to join our team in Arlington, VA (Hybrid) . This position is contingent upon award.

We are seeking a talented Data Engineer / Metadata Engineer to design, develop, and optimize data pipelines, metadata repositories, and data governance solutions that support enterprise analytics, reporting, and data management initiatives. This role will be responsible for ensuring data quality, discoverability, lineage, cataloging, and integration across a complex data ecosystem (both internal and external to supporting organization).

The ideal candidate combines strong technical data engineering skills with expertise in metadata management, data governance frameworks, and modern cloud data platforms.

Key Responsibilities

Data Engineering

• Design, build, and maintain scalable data pipelines and ETL/ELT processes.
• Integrate data from multiple structured and unstructured sources into enterprise data platforms.
• Integrate and correlate data sets both internal and external to customer organization.
• Develop and optimize data models, data warehouses, data lakes, and lakehouse architectures.
• Ensure data pipelines meet performance, reliability, and scalability requirements.
• Implement automation and monitoring for data ingestion and processing workflows.

Metadata Management

• Design and maintain enterprise metadata repositories and data catalogs.
• Define and manage business, technical, and operational metadata standards.
• Develop processes for automated metadata collection, classification, and enrichment.
• Maintain metadata lineage and impact analysis capabilities across data assets.
• Ensure metadata consistency and accuracy across enterprise systems.

Data Governance & Quality

• Support enterprise data governance initiatives and best practices.
• Partner with business and technical stakeholders to define data ownership and stewardship models.
• Implement data quality monitoring and validation controls.
• Ensure compliance with organizational data policies and regulatory requirements.
• Support master data management (MDM) and reference data initiatives.

Cloud & Platform Engineering

• Develop and support cloud-native data solutions within Azure, AWS, or Google Cloud environments.
• Build and optimize data integration solutions using cloud services and modern data tools.
• Support enterprise analytics, AI/ML, business intelligence workloads, and assist with build of automation-first pipelines.
• Contribute to infrastructure-as-code and data platform automation efforts.

Collaboration & Stakeholder Support

• Work closely with data architects, analysts, data scientists, governance teams, and business stakeholders.